Related papers: Enabling Spatial Digital Twins: Technologies, Chal…

Subsea exploration, inspection, and intervention operations heavily rely on remotely operated vehicles (ROVs). However, the inherent complexity of the underwater environment presents significant challenges to the operators of these…

The advancement of the Internet of Things (IoT) and Artificial Intelligence has catalyzed the evolution of Digital Twins (DTs) from conceptual ideas to more implementable realities. Yet, transitioning from academia to industry is complex…

Purpose: Digital twins are virtual interactive models of the real world, exhibiting identical behavior and properties. In surgical applications, computational analysis from digital twins can be used, for example, to enhance situational…

Traditional knowledge-based situation awareness (SA) modes struggle to adapt to the escalating complexity of today's Energy Internet of Things (EIoT), necessitating a pivotal paradigm shift. In response, this work introduces a pioneering…

Digital twins (DT) are increasingly used in healthcare to model patients, processes, and physiological systems. While recent solutions leverage visualization, visual analytics, and user interaction, these systems rarely incorporate…

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by…

Digital Twin technology is being envisioned to be an integral part of the industrial evolution in modern generation. With the rapid advancement in the Internet-of-Things (IoT) technology and increasing trend of automation, integration…

Virtual Reality technology, when integrated with Surgical Digital Twins (SDTs), offers significant potential in medical training and surgical planning. We present SurgTwinVR, a VR application that immerses users within an SDT and enables…

Digital network twins (DNTs) are virtual representations of physical networks, designed to enable real-time monitoring, simulation, and optimization of network performance. When integrated with machine learning (ML) techniques, particularly…

The complexity of cyberattacks in Cyber-Physical Systems (CPSs) calls for a mechanism that can evaluate critical infrastructures' operational behaviour and security without affecting the operation of live systems. In this regard, Digital…

Generative artificial intelligence (GAI) and digital twin (DT) are advanced data processing and virtualization technologies to revolutionize communication networks. Thanks to the powerful data processing capabilities of GAI, integrating it…

In intelligent transportation systems (ITSs), incorporating pedestrians and vehicles in-the-loop is crucial for developing realistic and safe traffic management solutions. However, there is falls short of simulating complex real-world ITS…

A Digital Twin (DT) is a digital representation of a physical object used to simulate it before it is built or to predict failures after the object is deployed. In this article, we introduce our approach, which applies the concept of a…

We present an uncertainty-aware Digital Twin (DT) for geologic carbon storage (GCS), capable of handling multimodal time-lapse data and controlling CO2 injectivity to mitigate reservoir fracturing risks. In GCS, DT represents virtual…

Network Digital Twins represent a key technology in future networks, expected to provide the capability to perform accurate analysis and predictions about the behaviour of 6G mobile networks. However, despite the availability of several…

A Digital Twin (DT) is a simulation of a physical system that provides information to make decisions that add economic, social or commercial value. The behaviour of a physical system changes over time, a DT must therefore be continually…

Over the recent years, the protection of the so-called `soft-targets', i.e. locations easily accessible by the general public with relatively low, though, security measures, has emerged as a rather challenging and increasingly important…

Insufficient data volume and quality are particularly pressing challenges in the adoption of modern subsymbolic AI. To alleviate these challenges, AI simulation uses virtual training environments in which AI agents can be safely and…

This chapter provides an introduction to the foundations of digital twins and makes the case for employing them in smart grids. As engineered systems become more complex and autonomous, digital twin technology gains importance as the…

The increasing capabilities of Digital Twins (DTs) in the context of the Internet of Things (IoT) and Industrial IoT (IIoT) call for seamless integration with simulation platforms to support system design, validation, and real-time…